Abstract Optimizing and extending advance care planning (ACP) is a pressing societal need in response to population aging. Medicare recognized this need, and in 2016 began to reimburse ACP visits. This project seeks to improve ACP by accomplishing two key goals. First, to determine the influence of end-of-life care preferences on patient-centered outcomes and the optimal time for ACP. Second, to determine the effectiveness of existing ACP practices in the Medicare population. ACP identifies and clarifies patients? values and expectations to formulate end-of-life treatment preferences which later inform treatment decisions at the end of life. Too often, though, ACP occurs in a data-vacuum. Providers struggle to accurately prognosticate and patients often misestimate how their preferences will influence outcomes. Therefore, we aim to inform data driven ACP by determining the association between end- of-life treatment preferences and both individual and caregiver outcomes. Only recently has the data needed to inform this critical question been collected. The National Health and Aging Trends Study (NHATS), a longitudinal survey of Medicare beneficiaries, obtained the first nationally representative data on end-of-life care preferences and how preferences change over time. Linkage from NHATS to other datasets will inform caregiver and end-of-life experiences amongst NHATS respondents. Our analyses will focus on disability and mortality at the individual level in addition to total caregiving time. Optimizing ACP also requires understanding when patients are most in need of ACP. Therefore, we will identify the clinical circumstances where individual preferences are most likely to change their preferences to identify times when ACP may be most valuable. Our second major goal is to understand the effectiveness of existing ACP. Specifically, we will identify patient, provider and system-level predictors of ACP visits and measure the relationship between ACP visits and patient-centered outcomes in a sample of the Medicare population. This proposal will serve as the basis for future patient-centered, data-driven ACP. This proposal will be particularly important for older adults with Alzheimer?s disease and related dementias (ADRD) because it will inform the optimal timing of ACP in patients with cognitive decline and better inform proxy decision makers. The results of this proposal can be immediately incorporated by clinicians into existing ACP and will inform researchers and policy-makers on how to optimize ACP in the future.